On the application of remote sensing towards the estimation of cultivated land lost to urbanization

In this research work, a 40-km² SPOT-5 High-Resolution Imagery (HRI) of the Warsak locality in district Peshawar, Pakistan, was utilized to approximate the quantity of cultivated land lost to urbanization, due to the construction of new homes and buildings. The imagery from a period of 2005 to 2015 for wheat crop was taken, specifically during the months of March and June when the crop is rich green and golden ripe respectively. eCognition ® program’s Object-Oriented Classification Method (OOCM) was employed for recognition of land versus buildings. Nearest Neighbour (NN), Support Vector Machine (SVM), Decision Trees (DT) and Random Forests (RF) were utilized for the classification process. The results demonstrated that the urbanized area had increased by approximately 28 per cent in the area considered. Moreover, the efficacy of the proposed method is depicted by an accuracy of 97.9 per cent and a Kappa Statistics of 0.975 for the SVM classifier.     

基于时频域的卷积神经网络运动想象脑电信号识别方法

针对目前运动想象脑电（EEG）信号识别率较低的问题，考虑到脑电信号蕴含着丰富的时频信息，提出一种基于时频域的卷积神经网络（CNN）运动想象脑电信号识别方法。首先，利用短时傅里叶变换（STFT）对脑电信号的相关频带进行预处理，并将多个电极的时频图组合构造出一种二维时频图；然后，针对二维时频图的时频特性，通过一维卷积的方法设计了一种新颖的CNN结构；最后，通过支持向量机（SVM）对CNN提取的特征进行分类。基于BCI数据集的实验结果表明，所提方法的平均识别率为86.5%，优于其他传统运动想象脑电信号识别方法；同时将该方法应用在智能轮椅上，验证了其有效性。     

Characterizing physical habitat preferences and thermal refuge occupancy of brook trout (Salvelinus fontinalis) and Atlantic salmon (Salmo salar) at high river temperatures

Anthropogenic influences, including climate change, are increasing river temperatures in northern and temperate regions and threatening the thermal habitats of native salmonids. When river temperatures exceed the tolerance levels of brook trout and Atlantic salmon, individuals exhibit behavioural thermoregulation by seeking out cold‐water refugia – often created by tributaries and groundwater discharge. Thermal infrared (TIR) imagery was used to map cold‐water anomalies along a 53 km reach of the Cains River, New Brunswick. Trout and salmon parr did not use all identified thermal anomalies as refugia during higher river temperature periods (>21°C). Most small‐bodied trout (8–30 cm) were observed in 80% of the thermal anomalies sampled. Large‐bodied trout (>35 cm) required a more specific set of physical habitat conditions for suitable refugia, that is, 100% of observed large trout used 30% of the anomalies sampled and required water depths >65 cm within or adjacent to the anomaly. Densities of trout were significantly higher within anomalies compared with areas of ambient river temperature. Salmon parr were less aligned with thermal anomalies at the observed temperatures, that is, 59% were found in 65% of the sampled anomalies; and densities were not significantly different within/ outside anomalies. Salmon parr appeared to aggregate at 27°C, and after several events over 27°C variability in aggregation behaviour was observed – some fish aggregated at 25°C, others did not. We stipulate this is due to variances of thermal fatigue. Habitat suitability curves were developed for velocity, temperature, depth, substrate, and deep water availability to characterize conditions preferred by fish during high‐temperature events. These findings are useful for managers as our climate warms, and can potentially be used as a tool to help conserve and enhance thermal refugia for brook trout and Atlantic salmon in similar systems.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

Validation of performance of real-time kinematic PPP. A possible tool for deformation monitoring

Structural failures (bridge or building collapses) and geohazards (landslides, ground subsidence or earthquakes) are worldwide problems that often lead to significant economic and loss of life. Monitoring the deformation of both natural phenomena and man-made structures is a major key to assessing structural dynamic responses. Actually, this monitoring process is under real-time demand for developing warning and alert systems.One of the most used techniques for real-time deformation monitoring is the Global Navigation Satellite System (GNSS) real-time procedure, where the relative positioning approach, using a well-known reference station, has been applied.This study was conducted to evaluate the actual quality of the real-time kinematic Precise Point Positioning (PPP) GNSS solution for deformation monitoring, where it can be concluded that a promise tool is under development and should be taken into account on actual and near future real-time deformation monitoring studies and applications.     

17-18世纪英文文献中的中国建筑意象

17—18世纪,伴随着蓬勃发展的全球贸易,欧洲掀起了一场波及诸多领域的"中国风"。在英国,从政治家、哲学家、文人等一代文化精英致力于翻译、编纂传入欧洲有关中国的文献,到全社会对自然风致园、"中国风"点景建筑的实践与讨论,再到18世纪末英国人出版直击中国的著作,存世的一系列英文文献、设计图纸中多有关涉中国古代建筑的信息。本文以时间脉络为轴,尽可能全面搜集17—18世纪在英传播的涉及中国古代建筑的文献史料,根据不同时间段因社会背景有异、对中国建筑认知的深度不同,初步作一分类。希望可以为今后明晰中国建筑意象在英国的内容变迁与英国本土政治、经济、文化等各方面互动联系的深入研究提供史料基础。     

Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques

Accurate and rapid assessment of the as-built status on any construction site provides the opportunity to understand the current performance of a project easily and quickly. Rapid project assessment further identifies discrepancies between the as-built and as-planned progress, and facilitates decision making on the necessary remedial actions. Currently, manual visual observations and surveying are the most dominant data capturing techniques but they are time-consuming, error-prone, and infrequent, making quick and reliable decision-making difficult. Therefore, research on new approaches that allow automatic recognition of as-built performance and visualization of construction progress is essential. This paper presents and compares two methods for obtaining point cloud models for detection and visualization of as-built status for construction projects: (1) A new method of automated image-based reconstruction and modeling of the as-built project status using unordered daily construction photo collections through analysis of Structure from Motion (SfM); (2) 3D laser scanning and analysis of the as-built dense point cloud models. These approaches provide robust means for recognition of progress, productivity, and quality on a construction site. In this paper, an overview of the newly developed automated image-based reconstruction approach and exclusive features which distinct it from other image-based or conventional photogrammetric techniques is presented. Subsequently the terrestrial laser scanning approach carried out for reconstruction and comparison of as-built scenes is presented. Finally the accuracy and usability of both of these techniques for metric reconstruction, automated production of point cloud models, 3D CAD shape modeling, and as-built visualizations is evaluated and compared on eight different case studies. It is shown that for precise defect detection or alignment tasks, image-based point cloud models may not be as accurate and dense as laser scanners' point cloud models. Nonetheless image-based point cloud models provide an opportunity to extract as-built semantic information (i.e., progress, productivity, quality and safety) through the content of the images, are easy to use, and do not need add burden on the project management teams by requiring expertise for data collection or analysis. Finally image-based reconstruction automatically provides photo alignment with point cloud models and enables image-based renderings which can remarkably impact automated performance monitoring and as-built visualizations.     

高分辨率卫星遥感影像在城市和工程中的应用潜力分析

本文结合最近完成的一个试验研究项目 ,对 1m分辨率IKONOS影像的几何精度、分辨率及影像质量进行初步评价 ,并分析它在城市和工程中应用的可能性和潜力。     

相互作用模型在城市规划中的运用

城市增长是未来几个世纪备受关注的问题。为了保证城市可持续发展，有必要对城市的发展进行监控，但预测城市的发展趋势需要一些空间信息的支持、卫星图像能够提供可靠的信息用来评定城市增长的不同状态，而预测未来的建设区段则更加重要。本文构建了相互作用模型（interaction models），或者更精确地说叫潜力模型（potential model），以确定城市空间的扩展方向。该模型被运用于法国斯特拉斯堡地区的分析，采用了两张遥感数据影像，一张用于模型处理，一张用于检验结果。另外，模型还运用GIS技术以提高准确度，同时还考虑到了交通网络。     

谈环境雕塑在城市建设中的意义

介绍了雕塑设计的要求和内容，分析了环境雕塑的发展演变过程以及具有的特征，探讨了环境雕塑在城市建设中具有的作用，表明了环境雕塑在城市空间环境景观设计中具有重要的意义。